Section outline

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    Modelling and AI for infectious disease control 2025

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    More information may appear later

    Course Instructors

    Niel Hens, Hasselt University and University Antwerp

    Pieter Libin, Vrije Universiteit Brussel


    Course contents:

    This course covers the following topics:

    • General introduction to epidemic modeling and reinforcement learning

    • Compartment and metapopulation models

    • Individual-based models

    • Practical session on metapopulation and individual-based models [Python]

    • Reinforcement learning: intuition and problem setting

    • Value functions, Q-learning (including Deep Q-Networks), and Policy gradient (including PPO).

    • Multi-armed bandits

    • Practical session on Q-learning [Python]

    • Policy optimisation for epidemic decision making

    • Use case: Q-learning in a metapopulation model [Python]


    Software: Python and a set of free software libraries

    Follow up: Homework projects for those interested


    Time and Place

    All lectures take place at Stockholm University in Campus Albano, house 1, level 2. See "    Registration and Venue" page for further details.

    Lecture times (includes also problem solving, tutorials, computer sessions, ...): 

    Monday June 23: 9.00-10.30, 11.00-12.30, 14.00-15.30, 16.00-17.30

    Tuesday June 24: 9.00-10.30, 11.00-12.30, 14.00-15.30, 16.00-17.30

    Wednesday June 25: 9.00-10.30, 11.00-12.30

    General prerequisites

    It is expected that course participants have basic knowledge of statistics and mathematics and rudimentary knowledge of infectious disease epidemiology. It is also expected that participants have basic computer software knowledge and preferably are familiar with the software R. 

    IMPORTANT: All participants are expected to bring a laptop with R installed on it.

    Additional prerequisites for this course

     Programming in a scripting language (such as R, Python)

    Relevant literature

    [1] http://incompleteideas.net/book/the-book-2nd.html

    [2] https://link.springer.com/chapter/10.1007/978-3-030-67670-4_10

    [3] https://link.springer.com/chapter/10.1007/978-3-030-10997-4_28



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    Sources for R

    Instructions for installing R, introduction to R?

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    Monday, June 24

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    Tuesday, June 25

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    Wednesday, June 26

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